Update app.py
#1
by
SuriRaja
- opened
app.py
CHANGED
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import fitz # PyMuPDF
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import cv2
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from pdf2image import convert_from_path
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import pytesseract
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import numpy as np
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import os
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from fpdf import FPDF
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# Convert PDFs to images
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def convert_pdf_to_images(pdf_path, dpi=300):
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images = convert_from_path(pdf_path, dpi=dpi, poppler_path="/usr/bin")
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return [cv2.cvtColor(np.array(image), cv2.COLOR_RGB2BGR) for image in images]
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# Align images
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def align_images(img1, img2):
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gray1 = cv2.cvtColor(img1, cv2.COLOR_BGR2GRAY)
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gray2 = cv2.cvtColor(img2, cv2.COLOR_BGR2GRAY)
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orb = cv2.ORB_create()
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kp1, des1 = orb.detectAndCompute(gray1, None)
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kp2, des2 = orb.detectAndCompute(gray2, None)
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bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
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matches = bf.match(des1, des2)
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matches = sorted(matches, key=lambda x: x.distance)
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src_pts = np.float32([kp1[m.queryIdx].pt for m in matches]).reshape(-1, 1, 2)
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dst_pts = np.float32([kp2[m.trainIdx].pt for m in matches]).reshape(-1, 1, 2)
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matrix, _ = cv2.findHomography(src_pts, dst_pts, cv2.RANSAC, 5.0)
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# Validate if alignment is good enough
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if matrix is None or len(matches) < 10: # Check if sufficient matches exist
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raise ValueError("Alignment failed. Insufficient matches between images.")
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aligned_img = cv2.warpPerspective(img2, matrix, (img1.shape[1], img1.shape[0]))
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return aligned_img
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# Compare images with noise reduction and filtering
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def compare_images(img1, img2):
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diff = cv2.absdiff(img1, img2)
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gray_diff = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)
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# Apply Gaussian blur to reduce noise
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blurred_diff = cv2.GaussianBlur(gray_diff, (5, 5), 0)
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# Apply thresholding
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_, thresh = cv2.threshold(blurred_diff, 40, 255, cv2.THRESH_BINARY)
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# Morphological operations to smooth out noise
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kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (5, 5))
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cleaned = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
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# Filter out small regions
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contours, _ = cv2.findContours(cleaned, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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filtered_mask = np.zeros_like(cleaned)
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for cnt in contours:
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if cv2.contourArea(cnt) > 100: # Ignore small differences (area < 100 pixels)
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cv2.drawContours(filtered_mask, [cnt], -1, 255, -1)
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return filtered_mask
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# Highlight changes
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def highlight_changes(img, mask):
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overlay = img.copy()
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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for cnt in contours:
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#
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def generate_comparison_pdf(original_pdf, edited_pdf):
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original_images = convert_pdf_to_images(original_pdf)
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edited_images = convert_pdf_to_images(edited_pdf)
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combined_images = []
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aligned_img = align_images(orig_img, edit_img)
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diff_mask = compare_images(orig_img, aligned_img)
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highlighted_img = highlight_changes(edit_img, diff_mask)
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# Ensure dimensions match
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height = min(orig_img.shape[0], highlighted_img.shape[0])
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orig_img_resized = orig_img[:height]
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highlighted_img_resized = highlighted_img[:height]
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combined_images.append(np.hstack((orig_img_resized, highlighted_img_resized)))
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output_path = "outputs/comparison_result.pdf"
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pdf = FPDF()
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for img in combined_images:
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pdf.add_page()
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pdf.image(temp_path, x=10, y=10, w=190)
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os.remove(temp_path)
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pdf.output(output_path)
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return output_path
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# Gradio interface function
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def pdf_comparison(original_pdf, edited_pdf):
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return "Error: File size exceeds 50 MB. Please upload smaller files."
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# Proceed with PDF comparison
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result_path = generate_comparison_pdf(original_pdf.name, edited_pdf.name)
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return result_path
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# Gradio interface
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interface = gr.Interface(
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gr.File(label="Upload Original PDF", file_types=[".pdf"]),
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gr.File(label="Upload Edited PDF", file_types=[".pdf"])
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],
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outputs=
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)
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if __name__ == "__main__":
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# Highlight changes and categorize small and large differences
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def highlight_changes(img, mask):
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overlay = img.copy()
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contours, _ = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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summary = []
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for cnt in contours:
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area = cv2.contourArea(cnt)
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x, y, w, h = cv2.boundingRect(cnt)
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if area > 500: # Major differences
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cv2.rectangle(overlay, (x, y), (x + w, y + h), (0, 0, 255), 2) # Red
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summary.append(f"Major Difference: Location=({x}, {y}), Size=({w}x{h}), Area={area}")
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elif 100 < area <= 500: # Small differences
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cv2.rectangle(overlay, (x, y), (x + w, y + h), (255, 0, 0), 2) # Blue
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summary.append(f"Small Difference: Location=({x}, {y}), Size=({w}x{h}), Area={area}")
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return overlay, summary
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# Generate comparison PDF with detailed summary
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def generate_comparison_pdf(original_pdf, edited_pdf):
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original_images = convert_pdf_to_images(original_pdf)
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edited_images = convert_pdf_to_images(edited_pdf)
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combined_images = []
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all_summaries = []
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for page_num, (orig_img, edit_img) in enumerate(zip(original_images, edited_images), start=1):
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aligned_img = align_images(orig_img, edit_img)
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diff_mask = compare_images(orig_img, aligned_img)
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highlighted_img, summary = highlight_changes(edit_img, diff_mask)
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# Add page number to summary
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page_summary = [f"Page {page_num}:"]
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page_summary.extend(summary)
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all_summaries.extend(page_summary)
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# Ensure dimensions match
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height = min(orig_img.shape[0], highlighted_img.shape[0])
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orig_img_resized = orig_img[:height]
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highlighted_img_resized = highlighted_img[:height]
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combined_images.append(np.hstack((orig_img_resized, highlighted_img_resized)))
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# Generate the PDF
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output_path = "outputs/comparison_result.pdf"
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pdf = FPDF()
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for img in combined_images:
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pdf.add_page()
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pdf.image(temp_path, x=10, y=10, w=190)
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os.remove(temp_path)
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# Add detailed summary to the PDF
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summary_path = "outputs/summary.txt"
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with open(summary_path, "w") as f:
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f.write("\n".join(all_summaries))
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pdf.add_page()
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pdf.set_font("Arial", size=12)
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pdf.multi_cell(0, 10, "\n".join(all_summaries))
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pdf.output(output_path)
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return output_path, summary_path
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# Gradio interface function
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def pdf_comparison(original_pdf, edited_pdf):
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return "Error: File size exceeds 50 MB. Please upload smaller files."
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# Proceed with PDF comparison
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result_path, summary_path = generate_comparison_pdf(original_pdf.name, edited_pdf.name)
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return result_path, summary_path
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# Gradio interface
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interface = gr.Interface(
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gr.File(label="Upload Original PDF", file_types=[".pdf"]),
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gr.File(label="Upload Edited PDF", file_types=[".pdf"])
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],
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outputs=[
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gr.File(label="Download Comparison Report"),
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gr.File(label="Download Detailed Summary")
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],
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)
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if __name__ == "__main__":
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